The present application relates generally to an improved data processing apparatus and method and more specifically to mechanisms for disambiguating natural language content based on private-public context analysis.
With the increased usage of computing networks, such as the Internet, humans are currently inundated and overwhelmed with the amount of information available to them from various structured and unstructured sources. However, information gaps abound as users try to piece together what they can find that they believe to be relevant during searches for information on various subjects. To assist with such searches, recent research has been directed to generating cognitive systems, such as cognitive search engines, Question and Answer (QA) systems, and the like, which may take an input a search request or question, analyze it, and return results indicative of the most probable matches to the search request or answer to the input question. These cognitive systems provide automated mechanisms for searching through large sets of sources of content, e.g., electronic documents, and analyze them in a manner that simulates human thought in order to generate a reasoned output.